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refactor(sft): share_backward_bb default True, share_cache_pool auto-derived

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- kt_share_backward_bb defaults to True (always saves memory)
- kt_share_cache_pool no longer reads from env var; defaults False,
  auto-set to True by trainer_config_process when gradient checkpointing
  is enabled

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
mrhaoxx 2026-04-09 20:10:38 +08:00
parent 020eb929f7
commit 5bfcb5f784
1 changed files with 4 additions and 4 deletions
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8
kt-kernel/python/sft/config.py
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@ -64,8 +64,8 @@ class KTConfig:
kt_expert_checkpoint_path: str | None = None
kt_num_gpu_experts: int | None = None
kt_skip_expert_loading: bool | None = None
kt_share_backward_bb: bool | None = None
kt_share_cache_pool: bool | None = None
kt_share_backward_bb: bool | None = None # default True — always saves memory
kt_share_cache_pool: bool | None = None # auto-set by trainer_config_process, not user-facing
# Cache
kt_max_cache_depth: int | None = None
@ -117,9 +117,9 @@ class KTConfig:
if self.kt_max_cache_depth is None:
self.kt_max_cache_depth = _env_int("ACCELERATE_KT_MAX_CACHE_DEPTH", 2)
if self.kt_share_backward_bb is None:
self.kt_share_backward_bb = _env_bool("ACCELERATE_KT_SHARE_BACKWARD_BB", False)
self.kt_share_backward_bb = _env_bool("ACCELERATE_KT_SHARE_BACKWARD_BB", True)
if self.kt_share_cache_pool is None:
self.kt_share_cache_pool = _env_bool("ACCELERATE_KT_SHARE_CACHE_POOL", False)
self.kt_share_cache_pool = False
if self.kt_use_lora_experts is None:
self.kt_use_lora_experts = _env_bool("ACCELERATE_KT_USE_LORA_EXPERTS", False)
if self.kt_lora_expert_num is None: